Nonprofit experiments including donation flows, volunteer signups, and cause-driven conversion optimization.
Across 2 nonprofit experiments, 50% resulted in a statistically significant win. Winning variants saw an average lift of +51.0%.
1 experiment was inconclusive, meaning the difference between control and variant was not statistically significant. Inconclusive results are still valuable — they tell you what doesn't move the needle, so you can focus testing effort elsewhere.
These results come from real A/B tests with sample sizes ranging from hundreds to millions of visitors. Use them to inform your own nonprofit testing strategy and avoid repeating experiments that have already been run.
Problem: Visual elements on the landing page aren't doing enough to communicate value, build trust, or guide users toward the next step.
Context: Without clear urgency signals, users delay their decision on the landing page, leading to drop-offs and abandoned sessions.
Save your own experiments, get AI-powered test ideas, and build on patterns from 2+ real tests.
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